1. Field of the Invention
The present invention generally concerns magnetic resonance tomography (MRT) as employed in medicine for examination of patients. The present invention concerns a method as well as an MRT system for implementation of the method that enable the acquisition of reduced-artifact or improved-resolution slice images that are displaced relative to one another in the z-gradient direction.
2. Description of the Prior Art
MRT is based on the physical phenomenon of nuclear magnetic resonance and has been successfully used as an imaging method for over 15 years in medicine and biophysics. In this examination modality, the subject is exposed to a strong, constant magnetic field. The nuclear spins of the atoms in the subject, which were previously randomly oriented, thereby align.
Radio-frequency energy can now excite these “ordered” nuclear spins to a specific oscillation. In MRT, this oscillation generates the actual measurement signal which is acquired by suitable reception coils. By the use of inhomogeneous magnetic fields generated by gradient coils, the measurement subject can be spatially coded in all three spatial directions. The method allows a free selection of the slice to be imaged, so that slice images of the human body can be acquired in all directions. MRT as a slice image method in medical diagnostics that is distinguished predominantly as a “non-invasive” examination method with a versatile contrast possibility. Due to the excellent ability to represent the soft tissue, MRT has developed into a method superior in many ways to x-ray computed tomography (CT). MRT today is based on the application of spin echo and gradient echo sequences that enable an excellent image quality with measurement times in the range of seconds to minutes.
For examination of larger segments of a patient, or for whole-body exposures, a continuous table displacement (move during scan, MDS) is used. In particular, the use of measurement device in connection with segmented imaging sequences such as, for example, a multi-shot TSE sequence (turbo spin echo, TSE) appears promising given whole-body examinations of metastases (whole-body metastasis screening). Despite the technical advances in the design of MRT apparatuses, resolution, acquisition time and signal-to-noise ratio (SNR) of an MRT image remain limiting factors with regard to the image quality, which presently (in particular in MDS-based imaging) inevitably lead to image artifacts as well as to residual apparatus-dependent artifacts.
One possibility to reduce movement artifacts known in the prior art is the application of accelerated MRT imaging methods, of which PPA (partial parallel acquisition) methods are examples. PPA is explained in the following:
As shown in FIG. 2, the acquisition of data in MRT occurs in k-space (frequency domain). The MRT image 25 in the image domain is linked with the MRT data 23 in k-space by means of Fourier transformation 24. The spatial coding of the subject which spans k-space occurs by means of gradients in all three spatial directions. In the case of 2D imaging, differentiation is thereby made between slice selection (establishes an acquisition slice in the subject, typically the z-axis), frequency coding (establishes a direction in the slice, typically the x-axis) and phase coding (determines the second dimension within the slice, typically the y-axis). In the case of 3D imaging, the slice selection is replaced by a second phase coding direction. Without limitation as to generality herein, two-dimensional Cartesian k-space is assumed, which is sampled line-by-line. The data of a single k-space line are frequency-coded by means of a gradient upon readout. Each line in k-space has the interval Δky that is generated by a phase coding step. Since the phase coding takes a great deal of time in comparison with the other spatial codings, many methods, including PPA, are based on a reduction of the number of time-consuming phase coding steps to shorten the image measurement time. The fundamental idea of PPA imaging is that the k-space data are not acquired by a single coil, but rather (according to FIG. 3A) by a (for example linear) arrangement of component coils (coil 1 through coil 4), a coil array. Each of the spatially-independent coils of the array carries certain spatial information which is used in order to achieve a complete spatial coding via a combination of the simultaneously-acquired coil data 26.1, 26.2, 26.3, 26.4. This means that a number of other unsampled lines 32 (shown dotted in white in the following figures) that are ordered in k-space can also be determined from a single acquired k-space line (shown in grey in the following figures).
PPA methods thus use spatial information that is contained in the components of a coil arrangement in order to partially replace the time-consuming phase coding that is normally generated using a phase gradient. The image measurement time is thereby reduced corresponding to the ratio of number of the lines of the reduced data set to the number of the lines of the conventional (thus completed) data set. In comparison to the conventional acquisition, in a typical PPA acquisition only a fraction (½, ⅓, ¼, etc.) of the phase coding lines are acquired. A special reconstruction is then applied to the data in order to reconstruct the missing k-space lines and thus to obtain the full field of view (FOV) image in a fraction of the time (FOV is the image region of interest to be acquired).
Different PPA methods use different reconstruction methods (which normally are algebraic methods). The best known PPA techniques are SMASH (simultaneous acquisition of spatial harmonics), SENSE (sensitivity encoding) and GRAPPA (generalized auto-calibration PPA).
In all PPA techniques the algebraic reconstruction of the missing k-space lines additionally requires identification of the respective component coil of each component coil participating in the measurement, which in FIG. 3 is symbolized by the arrow 28. A complete reconstruction of all k-space lines is possible only given knowledge of the coil sensitivities, and the image 25 in the spatial domain is obtained by subsequent Fourier transformation (arrow 27).
In the conventional PPA techniques, the determination of the coil sensitivities ensues by measurement of calibration scans, whether at the beginning of the measurement in the form of pre-scans or during the measurement in the form of integrated scans (ACS lines, autocalibration signals), that are represented in FIG. 4 as black k-space lines in the middle region of the k-matrix (k-space slice).
Although the coil sensitivities can be approximated well by only a few calibration scan lines from the middle region of the k-matrix (which predominantly contains contrast information), the measurement of calibration scan lines nevertheless significantly extends the total acquisition time and increases the degree of movement artifacts in the reconstructed image 25.
In the prior art it is possible to measure a slice to be acquired in the form of partial data sets of k-space which in their entirety again form a complete k-space data set, on the basis of which (averaged and/or filtered) the respective coil sensitivity of each component coil can then be determined by calculation. This PPA method has the object to even further reduce the total measurement time, by the measurement of calibration scan lines being omitted. The method is described in S. Kannengiesser et al., Proc. ISMRM 12, 2149 (2004). As described therein, a measurement of the same slice in the spatial domain ensues according to FIG. 6 by the measurement of a number (here two) of partial data sets of k-space 30, 31. In the first partial data set 30, only each odd line of the selected k-space slice (line 1, line 3, line 5 etc.) was acquired and only each even line (line 2, line 4, line 6 etc.) was acquired in the second partial data set 31. Taken together, the first partial data set 30 and the second partial data set 31 form a complete data set 32 of k-space. By the separation of the measurement into non-overlapping partial data sets, each partial data set separately represents a PPA data set that can be respectively reconstructed into a complete k-space data set by means of known PPA reconstruction methods (SMASH, SENSE, GRAPPA). The chronological order of the sampling of data set 32 is advantageously selected such that each partial data set 30, 31 separately contains the least possible movement artifacts so that, after the respective PPA reconstruction both reconstructed data sets are combined into an image, the final image ultimately contains minimal movement artifacts without forfeiting SNR. The division into non-overlapping partial data sets enables a calculation of the coil sensitivities necessary for the PPA reconstruction without having to acquire separate calibration scan lines therefor, which ultimately leads to a significantly shorter acquisition time.
Nonetheless, in such accelerated PPA-based MRT imaging methods resolution and movement- and apparatus-conditional inconsistencies, particularly given the acquisition of a number of slices displaced relative to one another in the z-direction (for example by continuous table displacement during the measurement), represent limiting factors that manifest themselves in residual artifacts in the spatially-resolved image.